Today the importance of life science and its related processes are undeniable. Modeling and control of these kind of processes are too complicate because of existence of delay in growth and also nonlinear behavior of ...
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ISBN:
(纸本)9781467355339
Today the importance of life science and its related processes are undeniable. Modeling and control of these kind of processes are too complicate because of existence of delay in growth and also nonlinear behavior of micro-organisms. Model predictive control is one of the most popular advanced controlling strategies in this industry, however its dependence on accurate model for predicting future input and output values is limitating. If there is a way that could predict the future values of the process properly, it is possible to overcome to the existing challenges. In this paper we design a model free predictive controller by using a trained recurrent neural network as a predictor for prediction stage at MPC and using GA for solving the associated optimization problem that result the optimal control signal sequence.
This paper presents an LMI based robust H-infinity control scheme for constrained systems with norm- bounded uncertainties. The uncertainties are incorporated in the evaluation of the H-infinity norm and the time-doma...
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This paper presents an LMI based robust H-infinity control scheme for constrained systems with norm- bounded uncertainties. The uncertainties are incorporated in the evaluation of the H-infinity norm and the time-domain constraints. The robust closed-loop properties inclusive of stability, H-infinity performance and the satisfaction of the time- domain constraints are discussed. Analysis and simulation results for a 2 DOF quarter-car model show possible improve- ments on ride comfort, while robustly respecting safety related constraints such as good road holding, limited suspension strokes and actuator saturation.
Discovering functional gene clusters based on gene expression data has been a widely-used method that offers a tremendous opportunity for understanding the functional genomics of a specific disease. Due to its strong ...
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Discovering functional gene clusters based on gene expression data has been a widely-used method that offers a tremendous opportunity for understanding the functional genomics of a specific disease. Due to its strong power of comprehending and interpreting mass of genes, plenty of studies have been done on detecting and analyzing the gene clusters for various diseases. However, more and more evidence suggest that human diseases are not isolated from each other. Therefore, it's significant and interesting to detect the common functional gene clusters driving the core mechanisms among multiple related diseases. There are mainly two challenges for this task: first, the gene expression from each disease may contain noise; second, the common factors underlying multiple diseases are hard to detect. To address these challenges, we propose a novel deep architecture to discover the mutual functional gene clusters across multiple types of diseases. To demonstrate that the proposed method can discover precise and meaningful gene clusters which are not directly obtainable from traditional methods, we perform extensive experimental studies on both synthetic and real datasets - public gene-expression data of three types of cancers. Experimental results show that the proposed approach is highly effective in discovering the mutual functional gene clusters.
Human interest input could greatly enhance the efficiency of the multi-robot exploration. However, most of the previous work did not take the intention of the operator into account. In this paper, a human interest ori...
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ISBN:
(纸本)9781479927456
Human interest input could greatly enhance the efficiency of the multi-robot exploration. However, most of the previous work did not take the intention of the operator into account. In this paper, a human interest oriented multi-robot exploration system is designed. The system is composed of a mobile base station and several robot explorers. A human interest oriented task allocation method is developed to enable these robot explorers to coordinate based on the operator's intention. Furthermore, an optimization index is proposed to balance the obedience, connectivity and explorability of the system; and the optimization problem is solved to generate the movements of the mobile base station and the robot explorers. Simulations and real-world experiments have demonstrate the effectiveness of the system and the efficiency of the exploration process.
Many researchers have studied connections between the problems of feedback control and of communicating over a channel with feedback. We study two such feedback communication schemes, and focus on properties such as p...
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ISBN:
(纸本)9781467357159
Many researchers have studied connections between the problems of feedback control and of communicating over a channel with feedback. We study two such feedback communication schemes, and focus on properties such as phase margin, robustness with respect to unmodeled time delays, and exogenous noise inputs. In particular, we study the impact of unstable poles in the encoder or decoder on these properties, as quantified by the Bode sensitivity integral.
A processes composed of sequences of local cyclic The theoretical prediction of the behavioral properties of periodic structures is less difficult than in the case of nonperiodic ones. That is because all the informat...
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A processes composed of sequences of local cyclic The theoretical prediction of the behavioral properties of periodic structures is less difficult than in the case of nonperiodic ones. That is because all the information needed to describe the entire structure is given by the elementary substructure itself and by the manner it repeats in the whole periodic structure. So, only a small portion of the structure (which includes the repeating substructure) needs to be considered to obtain the properties of the whole periodic structure. In that context, the contribution provides the discussion of some system periodicity issues, and is aimed at modeling and evaluation of relationships linking the system structure features with required system's functioning.
The bag of visual words model (BoW) and its variants have demonstrate their effectiveness for visual applications and have been widely used by researchers. The BoW model first extracts local features and generates the...
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The availability of reliable underwater positioning systems to localize one or more vehicles simultaneously based on information received on-board a support ship or an autonomous surface vessel is key to the operation...
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The availability of reliable underwater positioning systems to localize one or more vehicles simultaneously based on information received on-board a support ship or an autonomous surface vessel is key to the operation of some classes of AUVs. Furthermore, there is considerable interest in reducing the number of sensors involved in acoustic navigation/positioning systems to reduce the costs involved and the time consumed in the deployment, callibration, and recovery phases. Motivated by these considerations, in this paper we address the problem of single underwater target positioning based on measurements of the ranges between the target and a moving sensor at the sea surface, obtained via acoustic ranging devices. In particular, and speaking in loose terms, we are interested in determining the optimal geometric trajectory of the surface sensor that will, in a well defined sense, maximize the range-related information available for underwater target positioning. To this effect, an appropriate Fisher Information Matrix is defined and its determinant is maximized to yield the sensor trajectory that maximizes the accuracy of the target position estimate that can possibly be obtained with any unbiased estimator. It is shown that the optimal trajectory depends on the relative velocity of the sensor, the sampling time between measurements, and the number of measurements acquired for the FIM computation. Simulation examples illustrate the key results derived.
The Iterative Learning control (ILC) problem in which tracking is only required at a subset of isolated time points along the trial duration has recently gained significant attention since it addresses the practical n...
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